View source: R/read_many_files.R
read_many_shop | R Documentation |
This accepts a directory. It will use read_shop
to load every zip
in that folder, assuming they are all files downloaded from the SafeGraph shop. It will then row-bind together each of the subfiles, so you'll get a list where one entry all the normalization data row-bound together, another is all the patterns files, and so on.
.
Note that after reading in data, if gen_fips = TRUE
, state and county names can be merged in using data(fips_to_names)
.
read_many_shop( dir = ".", recursive = FALSE, filelist = NULL, start_date = NULL, keeplist = c("patterns", "normalization_stats.csv", "home_panel_summary.csv", "visit_panel_summary.csv", "brand_info.csv"), exdir = dir, cleanup = TRUE, by = NULL, fun = sum, na.rm = TRUE, filter = NULL, expand_int = NULL, expand_cat = NULL, expand_name = NULL, multi = NULL, naics_link = NULL, select = NULL, gen_fips = FALSE, silent = FALSE, ... )
dir |
Name of the directory the files are in. |
recursive |
Look for files in all subdirectories as well. |
filelist |
Optionally specify only a subset of the filename to read in. |
start_date |
A vector of dates giving the first date present in each zip file, to be passed to |
keeplist, exdir, cleanup |
Arguments to be passed to |
by, fun, na.rm, filter, expand_int, expand_cat, expand_name, multi, naics_link, select, gen_fips, silent, ... |
Other arguments to be passed to |
## Not run: # In the working directory we have two shop ZIP files, one for March and one for April. mydata <- read_shop(# I only want some of the sub-files keeplist = c('patterns','home_panel_summary.csv'), # For patterns, only keep these variables select = c('raw_visit_counts', 'region', 'bucketed_dwell_times', 'location_name'), # I want two aggregations of patterns - one of total visits by state ('region') # and another by location_name that has the dwell times for each brand multi = list( list(name = 'all', by = 'region'), list(name = 'location_dwells', by = 'location_name', expand_cat = 'bucketed_dwell_times', expand_name = 'bucketed_times') ), # Be sure to specify start_date for read_shop start_date = c(lubridate::ymd('2020-03-01'),lubridate::ymd('2020-04-01'))) # The result is a list with two items- patterns and home_panel_summary.csv # patterns itself is a list with two data.tables inside - 'all' and 'location_name', # aggregated as given. ## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.